Biology subjects

Aryee, M.

Publications and source records attributed to Aryee, M..

7 recordsLinked to original sources

bioRxiv2025

Bone Marrow Adipokine Mediates Hematopoietic Regeneration and Stem Cell Fitness

Bone marrow (BM) hematopoietic stem cells (HSCs) are exquisitely sensitive to cues from the BM microenvironment (ME), which is critical for their engraftment and regeneration following myeloablative stress. Retinoic acid signaling, acting on both HSCs and niche cells, has emerged as a central regulator of this process. Among ME components, BM adipocytes (BMAs), which can comprise up to 45% of BM volume and expand dramatically during the pancytopenic phase after myeloablation, play a previously underappreciated role in hematopoietic recovery. Here, we identify retinoid X receptor (RXR) signaling in BMAs as a key regulator of the adipokine Resistin, which promotes HSC self-renewal and functional fitness by activating NF-{kappa}B signaling. Conditional loss of RXR in adiponectin-expressing cells suppressed Resistin production, resulting in reduced NF-{kappa}B activity in HSCs, impaired self-renewal, and defective multilineage hematopoietic regeneration. Functionally, in vivo Resistin neutralization impaired hematopoietic reconstitution, whereas supplementation with either monomeric or dimeric Resistin enhanced HSC self-renewal and long-term lympho-hematopoietic reconstitution in an NF-{kappa}B-dependent manner. Together, these findings establish BMA-derived Resistin as an RXR-dependent, critical extrinsic regulator of HSC self-renewal and regenerative hematopoiesis, underscoring its essential role in lympho-myeloid reconstitution after myeloablation. Disclosures: The authors declare no relevant conflicts of interest.

physiology↗

bioRxiv2025

Integrating Single-Cell Biophysical and Transcriptomic Features to Resolve Functional Heterogeneity in Mantle Cell Lymphoma

Intra-tumor heterogeneity impacts disease progression and therapeutic resistance but remains poorly characterized by conventional histologic, immunophenotypic, and molecular approaches. Single-cell biophysical properties distinguish functional phenotypes complementary to these approaches, providing additional insight into cellular diversity. Here we link both buoyant mass and stiffness to gene expression to identify clinically relevant phenotypes within primary mantle cell lymphoma (MCL) cells, employing MCL as a model of biological and clinical diversity in human cancer. Linked measurements reveal that buoyant mass and stiffness characterize B-cell development states from naive to plasma cell and correlate with expression of oncogenic B-cell receptor signaling genes such as BLK and CD79A. Additionally, changes in cell buoyant mass within primary patient specimens ex vivo correlate with sensitivity to Brutons Tyrosine Kinase inhibitors in vivo in MCL and chronic lymphocytic leukemia, another B-cell malignancy. These findings highlight the value of biophysical properties as biomarkers of response in pursuit of future precision therapeutic strategies.

cancer biology↗

bioRxiv2023

Dysregulated Repeat Element Viral-like Immune Response in Hepatocellular Carcinoma

PurposeHepatocellular carcinoma (HCC) is a lethal malignancy driven by complex interactions between cancer cells, immune cells, and additional stromal cells in the tumor microenvironment (TME). The LINE1 retrotransposon is a ubiquitous repeat RNA whose de-repression leads to significant cancer cell-intrinsic and TME changes that promote aggressive tumor characteristics. We leveraged single cell spatial transcriptomic profiling to characterize the relationship between LINE1 and differences in the heterogeneous HCC TME. Experimental DesignWe applied our profiling methodology to a cohort of 23 tissue specimens collected from patients who had undergone liver resection or transplantation and validated it in a partially-overlapping similar cohort of 39 specimens using RNA in-situ hybridization (RNA-ISH). ResultsWe found that LINE1-high tumors and LINE1-high single HCC cells exhibited a de-differentiated, stem-like, and inflammatory phenotype. Furthermore, within individual tumors, LINE1 high cancer cells associated spatially with one another and excluded the larger, organized immune cell conglomerates seen in LINE1 low tumors. Finally, we found that LINE1 RNA expression correlated with worse overall survival in the larger expanded retrospective cohort. ConclusionsOur study is the first to show a clearly disorganized immune TME in HCC driven by LINE1 expression, and this observation correlated with poor survival for patients whose tumors expressed large amounts of the LINE1 repeat RNA. These results provide further evidence of how effective anti-tumor immune responses contribute to cures after definitive surgery and may lead to novel biomarkers or drug targets in HCC. TRANSLATIONAL RELEVANCEThe viral-like LINE1 retrotransposon is known to influence tumor cell state and the immune response in a variety of cancer. Here, we have used single cell spatial transcriptomic profiling to resolve repeat and coding gene RNA expression in a cohort of hepatocellular carcinoma (HCC) patients. LINE1 RNA expression in HCC tumor cells was correlated with an undifferentiated stem-like cancer state and a disorganized, sparse immune infiltrate. Using in situ hybridization on an expanded validation cohort, we noted significantly worsened survival in the LINE1 high group. Altogether, LINE1 repeat RNA is a tumor intrinsic biomarker of more aggressive features that can be used for risk stratification and a potential biomarker for response to immunotherapies that merits further investigation.

cancer biology↗

bioRxiv2021

Gene clustering coordinates transcriptional output of disparate biological processes in eukaryotes

The establishment of distinct transcriptional states entails coordinated transcriptional coregulation of several disparate biological processes (BP), involving thousands of genes scattered throughout the genome. Linear clustering of genes in a single BP is one strategy for their transcriptional coregulation. However, whether such gene clustering also plays a role in transcriptional coherence of several disparate BPs remains unexplored. Here, by analyzing the genomes of eukaryotes ranging from yeast to human, we report the identification of thousands of conserved and species-specific disparate clustered BP pairs, many of which in normal human tissues are transcriptionally correlated. Strikingly, our results reveal that often this system-level transcriptional coordination is achieved in part by the genic proximity of regulatory nodes of disparate BPs whose coregulation drives the transcriptional coherence of their respective pathways. This, we hypothesize, is one strategy for creating coregulated, tunable modulons in eukaryotes.

systems biology↗

bioRxiv2021

Global-scale CRISPR gene editor specificity profiling by ONE-seq identifies population-specific, variant off-target effects

Defining off-target profiles of gene-editing nucleases and CRISPR base editors remains an important challenge for use of these technologies, therapeutic or otherwise. Existing methods can identify off-target sites induced by these gene editors on an individual genome but are not designed to account for the broad diversity of genomic sequence variation that exists within populations of humans or other organisms. Here we describe OligoNucleotide Enrichment and sequencing (ONE-seq), a novel in vitro method that leverages customizable, high-throughput DNA synthesis technology instead of purified genomic DNA (gDNA) from individual genomes to profile gene editor off-target sites. We show that ONE-seq matches or exceeds the sensitivity of existing single-genome methods for identifying bona fide CRISPR-Cas9 off-target sites in cultured human cells and in vivo in a liver-humanized mouse model. In addition, ONE-seq outperforms existing best-in-class single-genome methods for defining off-target sites of CRISPR-Cas12a nucleases, cytosine base editors (CBEs), and adenine base editors (ABEs), unveiling previously undescribed bona fide off-target sites for all these editors in human cells. Most importantly, we leveraged ONE-seq to generate the first experimentally-derived population-scale off-target profiles for Cas9 nucleases that define the impacts of sequence variants from >2,500 individual human genome sequences in the 1000 Genomes Project database. Notably, some of the variants we identified that lead to increased mutation frequencies at off-target sites are enriched in specific human populations. We validated that novel population-specific, variant-sensitive off-target sites nominated by ONE-seq in vitro can show increased frequencies of mutations in human lymphoblastoid cells (LCLs) harboring these sequence variants. Collectively, our results demonstrate that ONE-seq is a highly sensitive off-target nomination method that can uniquely be used to identify population subgroup-linked differences in off-target profiles of gene editors. ONE-seq provides an important new pathway by which to assess the impacts of global human genetic sequence diversity on the specificities of gene editors, thereby enabling a broader and more all-inclusive approach for profiling off-target effects of these transformative therapeutic technologies.

molecular biology↗

bioRxiv2017

hichipper: A preprocessing pipeline for assessing library quality and DNA loops from HiChIP data

Mumbach et al. recently described HiChIP, a novel protein-mediated chromatin conformation assay that lowers cellular input requirements while simultaneously increasing the yield of informative reads compared to previous methods (1). To facilitate the dissemination and adoption of this assay, we introduce hichipper (http://aryeelab.org/hichipper), an open-source HiChIP data preprocessing tool, with features that include bias-corrected peak calling, library quality control, DNA loop calling, and output of processed data for downstream analysis and visualization (Figure 1a).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC=\"FIGDIR/small/192302_fig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@1d3d143org.highwire.dtl.DTLVardef@14fb9eforg.highwire.dtl.DTLVardef@1381541org.highwire.dtl.DTLVardef@fb6114_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO a) Overview of the hichipper analysis pipeline. hichipper requires aligned and annotated in-teraction files from preprocessing tools such as Hi-C Pro (2) as well as a .bed file of restriction sites. The hichipper pipeline identifies loop anchors using a background model that accounts for the effect of restriction site proximity on read density. The output of hichipper can be used for quality control, visualization, and downstream topology analysis of HiChIP data. b) Ratio of per-base coverage to local MACS-estimated local window background signal as a function of distance to nearest MboI cutsite for a HiChIP sample (blue) and a ChIP-seq sample (red). Both samples represent published mouse ESC with SMC1 (cohesin) ChIP. C_FIG

bioinformatics↗

bioRxiv2016

diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data

The three-dimensional architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in loop structure are associated with differences in gene expression and cell state. Here, we introduce diffloop, an R/Bioconductor package for identifying differential DNA looping between samples. The package additionally provides a suite of functions for the quality control, statistical testing, annotation and visualization of DNA loops. We demonstrate this functionality by detecting differences in DNA loops between ENCODE ChIA-PET datasets and relate looping to differences in epigenetic state and gene expression.

bioinformatics↗